ArticleNeurosurgical review2023
Whole-tumor histogram analysis of multi-parametric MRI for differentiating brain metastases histological subtypes in lung cancers: relationship with the Ki-67 proliferation index.
Article in Neurosurgical review, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 10 citations in OpenAlex.
- ADC Histogram Features of Breast Cancer Brain Metastases as Candidate Imaging Biomarkers of Primary Tumor ER, PR, Ki-67, and Luminal Status.Diagnostics (Basel, Switzerland) · 2026Article
- Histogram analysis based on contrast-enhanced T1-weighted imaging in pituitary macroadenomas: relation to histological subtype and expression.Quantitative imaging in medicine and surgery · 2026Article
- Evaluation of Lumbar Intervertebral Disc and Facet Joint Degeneration Using Histogram Analysis of T2 and T2* Values.JOR spine · 2025Article
- Machine learning model for preoperative classification of stromal subtypes in salivary gland pleomorphic adenoma based on ultrasound histogram analysis.BMC oral health · 2025Article
- Dual-energy CT combined with histogram parameters in the assessment of perineural invasion in colorectal cancer.International journal of colorectal disease · 2025Article
- Noninvasive prediction of Ki-67 expression level in IDH-wildtype glioblastoma using MRI histogram analysis: comparison and combination of MRI morphological features.Frontiers in oncology · 2025Article
- Visualizing the vascular-cellular microenvironment in lung cancer brain metastasis via multiparametric fusion of DCE-MRI and DWI.Frontiers in oncology · 2025Article
- The value of whole tumor apparent diffusion coefficient histogram parameters in predicting meningiomas progesterone receptor expression.Neurosurgical review · 2024Article
- Whole-tumor histogram analysis of postcontrast T1-weighted and apparent diffusion coefficient in predicting the grade and proliferative activity of adult intracranial ependymomas.Neuroradiology · 2024Article
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10 authors at 2 institutions in 1 country.
Funding
Abstract
This study aims to investigate the predictive value of preoperative whole-tumor histogram analysis of multi-parametric MRI for histological subtypes in patients with lung cancer brain metastases (BMs) and explore the correlation between histogram parameters and Ki-67 proliferation index. The preoperative MRI data of 95 lung cancer BM lesions obtained from 73 patients (42 men and 31 women) were retrospectively analyzed. Multi-parametric MRI histogram was used to distinguish small-cell lung cancer (SCLC) from non-small cell lung cancer (NSCLC), and adenocarcinoma (AC) from squamous cell carcinoma (SCC), respectively. The T1-weighted contrast-enhanced (T1C) and apparent diffusion coefficient (ADC) histogram parameters of the volumes of interest (VOIs) in all BMs lesions were extracted using FireVoxel software. The following histogram parameters were obtained: maximum, minimum, mean, standard deviation (SD), variance, coefficient of variation (CV), skewness, kurtosis, entropy, and 1st-99th percentiles. Then investigated their relationship with the Ki-67 proliferation index. The skewness-T1C, kurtosis-T1C, minimum-ADC, mean-ADC, CV-ADC and 1st - 90th ADC percentiles were significantly different between the SCLC and NSCLC groups (all p < 0.05). When the 10th-ADC percentile was 668, the sensitivity, specificity, and accuracy (90.80%, 76.70% and 86.32%, respectively) for distinguishing SCLC from NSCLC reached their maximum values, with an AUC of 0.895 (0.824 - 0.966). Mean-T1C, CV-T1C, skewness-T1C, 1st - 50th T1C percentiles, maximum-ADC, SD-ADC, variance-ADC and 75th - 99th ADC percentiles were significantly different between the AC and SCC groups (all p < 0.05). When the CV-T1C percentiles was 3.13, the sensitivity, specificity and accuracy (75.00%, 75.60% and 75.38%, respectively) for distinguishing AC and SCC reached their maximum values, with an AUC of 0.829 (0.728-0.929). The 5th-ADC and 10th-ADC percentiles were strongly correlated with the Ki-67 proliferation index in BMs. Multi-parametric MRI histogram parameters can be used to identify the histological subtypes of lung cancer BMs and predict the Ki-67 proliferation index.
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